Triple
T16360381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Incheon |
E397293
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Siheung |
E425371
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Siheung | Statement: [Incheon, borderedBy, Siheung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siheung Context triple: [Incheon, borderedBy, Siheung]
-
A.
Siheung
chosen
Siheung is a coastal city in northwestern South Korea known for its industrial complexes, wetlands, and proximity to Seoul.
-
B.
Icheon
Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
-
C.
Uijeongbu
Uijeongbu is a city in South Korea known as a suburban hub north of Seoul, featuring residential districts, commercial centers, and a history of hosting U.S. military bases.
-
D.
Anseong
Anseong is a city in Gyeonggi Province, South Korea, known for its traditional culture, agricultural heritage, and annual Baudeogi Festival.
-
E.
Sangil
Sangil are an indigenous Moro ethnolinguistic group of the southern Philippines and nearby Indonesian islands, known for their seafaring traditions and Islamic faith.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad241848190a9f32c7b050f20a5 |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00606fe9dc8190a336dc17f16f0ab4 |
completed | May 10, 2026, 10:39 a.m. |
Created at: April 10, 2026, 5:08 a.m.